Sparse Vegetation Coverage Information Extraction And Analysis Of Temporal And Spatial Variation Of Arid Desert In Xinjiang

Firstly, the definition of the vegetation coverage is given, and we discuss the significance of the vegetation coverage-. analysis of the advantages of remote sensing to monitor vegetation coverage and particularity of the sparse desert vegetation. Then, we discuss the research status of the vegetation coverage at home and abroad, and by this we discoved there is no special-purpose methods to abstract the vegetation coverage of the arid desert region. From this perspective, the comparison of different methods in desert areas will be essential way to find one feasible and suitable method of desert vegetation coverage information extraction at the larger scale within remote sensing.So we summarize all kinds of the vegetation coverage extract methods, and discuss the usage and scope of them, by this we find out six commonly used methods extraction methods of remote sensing (Modified maximal gradient difference model (Modified TGDVI), Pixel dichotomy model (PDM), Linear Spectral Unmixing (LSU) and vegetation index model (NDVI, EVI, MSAVI2)) were used to extract the vegetation fraction from MODIS images and the results were tested by observed data at field. It indicated that methods of vegetation index were mostly depends on the amount of observed values, so them had different results. EVI which considered the factors of atmosphere and soil had the highest simulation accuracy while NDVI had the lowest accuracy of results as it only considered red and near-infrared radiation. Because it’s difficult to extract pure desert vegetation pixel from MODIS images, using pixel values of crops instead of desert vegetation pixel could decreased the accuracy of PDM and LSU. With the better accuracy(R2=0.74; RMSE=13.46),modified TGDVI could dramatically reflect the vegetation fraction differences between the northern and southern desert in Xinjiang, and was the appropriate vegetation coverage information extraction method in such large scale of desert areas.In order to monitor the dynamic changes of vegetation coverage of desert in Xinjiang, we use Modified TGDVI to extract the vegetation coverage from2001to2010in desert of Xinjiang. Using the maximum synthesis MVC(Maximum Value Composites) and a linear regression analysis to analyze the variation of the vegetation in the desert region of Xinjiang in the past10years, then from the perspective of climate factors, we analyze the reason of vegetation coveage change in the study area. The result indicated that the vegetation coverage in study eara appear growth in a fluctuant way between2001and2007, there is a sharp decline between2007and2009, reached the minimum of10years, and a dramatic rise in2010which reached the maximum of10yeas, so there is a "v"shape change between2007and2010. There is also larger spatial difference in vegetation caverage change in the study area, small change is exist in lower vegetation coverage erea,like desert of east region and Taklimakan Desert, the vegetation in eastern Gribantunggut Desert and Ulungur watershed have siginificantly improved in the past10years, but there is serious vegetation degradation in west of Gurbantunggut Desert.By analyzing the relationship between climatic factots and vegetation coverage change we can know that the influence of temperature on vegetation coverage change results in controlling the metrical of annual vegetation growth and prolonging the spring growth period of vegetation, annual precipitation is the main factor in impacting of vegetationg coverage change.